Research Methods for Criminal Justice and Criminology, 6th...

Licensed to:

© 2011, 2008 Wadsworth, Cengage Learning

ALL RIGHTS RESERVED. No part of this work covered by the copyright herein may be reproduced, transmitted, stored, or used in any form or by any means graphic, electronic, or mechanical, including but not limited to photocopying, recording, scanning, digitizing, taping, Web distribution, information networks, or information storage and retrieval systems, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the publisher.

Library of Congress Control Number: 2010927231

ISBN-13: 978-0-495-81169-5ISBN-10: 0-495-81169-6

Wadsworth20 Davis DriveBelmont, CA 94002-3098USA

Cengage Learning is a leading provider of customized learning solutions with offi ce locations around the globe, including Singapore, the United Kingdom, Australia, Mexico, Brazil, and Japan. Locate your local offi ce at www.cengage.com/global.

Cengage Learning products are represented in Canada by Nelson Education, Ltd.

To learn more about Wadsworth, visit www.cengage.com/wadsworth Purchase any of our products at your local college store or at our pre-ferred online store www.cengagebrain.com.

Research Methods for Criminal Justice and Criminology, Sixth Edition

Michael G. Maxfi eld and Earl R. Babbie

Senior Publisher: Linda Schreiber-Ganster

Senior Acquisitions Editor: Carolyn Henderson Meier

Assistant Editor: Erin Abney

Media Editor: Ting Jian Yap

Senior Marketing Manager: Michelle Williams

Marketing Assistant: Jillian Myers

Senior Marketing Communications Manager: Laura Localio

Content Project Manager: Christy Frame

Creative Director: Rob Hugel

Senior Art Director: Maria Epes

Senior Print Buyer: Karen Hunt

Rights Acquisitions Account Manager, Text and Images: Don Schlotman

Production Service: Eve Malakoff -Klein, Cadmus Communications

Copy Editor: Susan Zorn

Interior Designer: Diane Beasley

Cover Designer: Riezebos Holzbaur Design Group

Cover Image: Michael Kelley/Getty Images

Compositor: Cadmus Communications

For product information and technology assistance, contact us atCengage Learning Customer & Sales Support, 1-800-354-9706.

For permission to use material from this text or product, submit all requests online at www.cengage.com/permissions.

Further permissions questions can be e-mailed to [email protected]

Printed in the United States of America1 2 3 4 5 6 7 14 13 12 11 10

Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).

Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.

Licensed to:

1

Part One

An Introduction to Criminal Justice Inquiry

What comes to mind when you encoun-ter the word science? What do you think of when we describe criminal justice as a social science? For some people, science is mathematics; for others, it is white coats and laboratories. Some confuse it with technology or equate it with diffi cult high school or college courses.

Science is, of course, none of these things per se, but it is diffi cult to specify exactly what science is. Scientists, in fact, disagree on the proper defi nition. Some object to the whole idea of social science; others question more specifi cally whether criminal justice can be a social science. For the purposes of this book, we view science as a method of inquiry—a way of learning and know-ing things about the world around us. Like other ways of learning and knowing about the world, science has some special charac-teristics. We’ll examine these traits in this opening set of chapters. We’ll also see how the scientifi c method of inquiry can be ap-plied to the study of crime and criminal justice.

Part One lays the groundwork for the rest of the book by examining the funda-mental characteristics and issues that make science different from other ways of know-ing things. Chapter 1 begins with a look

at native human inquiry, the sort of thing all of us have been doing all our lives. Be-cause people sometimes go astray in try-ing to understand the world around them, we’ll consider the primary characteristics of scientifi c inquiry that guard against those errors.

Chapter 2 deals specifi cally with the so-cial scientifi c approach to criminal justice inquiry and the links between theory and research. The lessons of Chapter 1 are ap-plied in the study of crime and criminal jus-tice. Although special considerations arise in studying people and organizations, the basic logic of all science is the same.

Ethics is one of these special consid-erations we face in studying people. In Chapter 3, we’ll see that most ethical ques-tions are rooted in two fundamental prin-ciples: (1) Research subjects should not be harmed, and (2) their participation must be voluntary.

The overall purpose of Part One, there-fore, is to construct a backdrop against which to view more specifi c aspects of re-search design and execution. By the time you complete the chapters in Part One, you’ll be ready to look at some of the more concrete aspects of criminal justice research.



Licensed to:

2

Chapter 1

Crime, Criminal Justice, and Scientifi c InquiryPeople learn about their world in a variety of ways, and they often make mistakes along the way. Science is different from other ways of learning and knowing. We’ll consider the foundations of social science, different purposes of research, and different general approaches to social science.

Learning Objectives 1. Understand why knowledge of research methods is valuable to criminal justice

professionals. 2. Describe the different ways we know things. 3. Distinguish inquiry as a natural human activity from inquiry through systematic

empirical research. 4. Recognize that much of our knowledge is based on agreement rather than on direct

experience. 5. Explain how tradition and authority are important sources of knowledge. 6. Understand how science tries to avoid errors by making observation a careful,

deliberate activity. 7. Describe why scientists use replication. 8. Recognize how ideological and political beliefs can infl uence research fi ndings. 9. Summarize three fundamental features of social science: theory, data collection,

and data analysis.10. Describe why social scientists are interested in explaining aggregates, not individuals.11. Understand that social scientists are primarily interested in discovering

relationships that connect variables.12. Understand the difference between idiosyncratic and nomothetic explanations.

(continued)



Licensed to:

Chapter 1 Crime, Criminal Justice, and Scientifi c Inquiry 3

Introduction 4

What Is This Book About? 5

Two Realities 5The Role of Science 7

Personal Human Inquiry 7Tradition 8

ARREST AND DOMESTIC VIOLENCE 8

Authority 8

Errors in Personal Human Inquiry 10

Inaccurate Observation 10Overgeneralization 10Selective Observation 11Illogical Reasoning 11Ideology and Politics 11To Err Is Human 12

Foundations of Social Science 12Theory, Not Philosophy or Belief 12Regularities 14

What About Exceptions? 14Aggregates, Not Individuals 14A Variable Language 15Variables and Attributes 16Variables and Relationships 17

Purposes of Research 19Exploration 19Description 20Explanation 20Application 21

Differing Avenues for Inquiry 21Idiographic and Nomothetic

Explanations 22Inductive and Deductive Reasoning 23

PUTTING IT ALL TOGETHER: “DRIVING WHILE BLACK” 24

Quantitative and Qualitative Data 25

Knowing Through Experience: Summing Up and Looking Ahead 27

Summary 27

Home DetentionHome detention with electronic monitoring (ELMO) was widely adopted as an alterna-tive punishment in the United States in the 1980s. The technology for this new sanction was made possible by advances in telecommu-nications and computer systems. Prompted by growing prison and jail populations, not to men-tion sales pitches by equipment manufacturers, criminal justice officials embraced ELMO. Ques-tions about the effectiveness of these programs

13. Distinguish between inductive and deductive forms of reasoning.14. Distinguish between quantitative or qualitative.

quickly emerged, however, and led to research to determine whether the technology worked. Comprehensive evaluations were conducted in Marion County (Indianapolis), Indiana. Se-lected findings from these studies illustrate the importance of understanding research methods in general and the meaning of various ways to measure program success in particular. ELMO programs directed at three groups of people were studied: (1) convicted adult offenders, (2) adults charged with a crime and awaiting



Licensed to:

4 Part One An Introduction to Criminal Justice Inquiry

trial, and (3) juveniles convicted of burglary or theft. People in each of the three groups were assigned to home detention for a specified time. They could complete the program in one of three ways: (1) successful release after serving their term; (2) removal due to rule violations, such as being arrested again or violating pro-gram rules; or (3) running away, or “abscond-ing.” The agencies that administered each pro-gram were required to submit regular reports to county officials on how many individuals in each category completed their home detention terms. The table below summarizes the pro-gram completion types during the evaluation study:

Convicted Pretrial Adults Adults Juveniles

Success 81% 73% 99%Rule violation 14 13 1Abscond 5 14 0

These figures, reported by agencies to county officials, indicate that the juvenile pro-gram was a big success; virtually all juveniles were successfully released.

Now consider some additional information on each program collected by the evaluation team. Data were gathered on new arrests of program participants and on the number of success-ful com-puterized telephone calls to participants’ homes:

Convicted Pretrial Adults Adults Juveniles

New arrest 5% 1% 11%Successful calls 53 52 17

As the above table shows, many more juveniles were arrested, and juveniles successfully an-swered a much lower percentage of telephone calls to their homes. What happened?

The simple answer is that the staff respon-sible for administering the juvenile program were not keeping track of offenders. The ELMO equipment was not maintained properly, and police were not visiting the homes of juveniles as

rr r ee

fff fffggg,,------ssnn--n

ss

planned. Because staff were not keeping track of program participants, they were not aware that many juveniles were violating the conditions of home detention. And because they did not detect violations, they naturally reported that the vast majority of young burglars and thieves completed their home detention successfully.

A county official who relied on only agency reports of program success would have made a big mistake in judging the juvenile program to be 99 percent successful. In contrast, an in-formed consumer of such reports would have been skeptical of a 99 percent success rate and searched for more information.

Adapted from Maxfield and Baumer (1991) and Baumer, Maxfield, and Mendelsohn (1993).

IntroductionCriminal justice professionals are both consumers and producers of research.

Spending a semester studying criminal justice research methodology may not be high on your list of “Fun Things to Do.” Perhaps you are or plan to be a criminal justice professional and are thinking, “Why do I have to study research methods? When I graduate, I’ll be working in probation (or law enforcement, or corrections, or court services), not conducting research! I would benefi t more from learning about proba-tion counseling (or police management, or cor-rections policy, or court administration).” Fair enough. But as a criminal justice professional, you will need to at least be a consumer of re-search. One objective of this book is to help you become an informed consumer of research. As we will soon see, justice professionals often produce research as well.

For example, in the section “Two Realities,” we will see how fi ndings from one of the fi rst ex-perimental studies of policing appeared to con-tradict a traditional tenet of law enforcement—that a visible patrol force prevents crime. Acting as a consumer of research fi ndings, a police offi cer, supervisor, or executive should be able



Licensed to:


to understand how the research was conducted and how the study’s fi ndings might apply in his or her department. Because police practices vary from city to city, a police executive would benefi t from being aware of research methods and knowing how to interpret fi ndings.

Most criminal justice professionals, espe-cially those in supervisory roles, routinely review various performance reports and statistical tab-ulations. In the past 30 years or so, thousands of criminal justice research and evaluation stud-ies have been conducted. The National Criminal Justice Reference Service (http://www.ncjrs.gov) was established in 1972 to archive and distrib-ute research reports to criminal justice profes-sionals and researchers around the world. Many such reports are prepared specifi cally to keep the criminal justice community informed about new research developments. More recently, the Center for Problem-Oriented Policing (POP Center, http://www.popcenter.org) was created to share applied research on varieties of law en-forcement problems. By understanding research methods, decision makers are better equipped to critically evaluate research reports and to recognize when methods are properly and im-properly applied. The vignette, “Home Deten-tion,” at the start of this chapter, describes an example of how knowledge of research methods can help policy makers avoid mistakes.

Another objective of this book is to help you produce research. In other courses you take or in your job, you may become a producer of research. For example, probation offi cers sometimes test new approaches to supervising or counseling cli-ents, and police offi cers try new methods of ad-dressing particular problems, or working with the community. Many cities and states have a compelling need to assess how changes in sen-tencing policy might affect jail and prison popu-lations. Determining whether such changes are effective is an example of applied research. A problem-solving approach, rooted in systematic research, is being used in more and more police departments and in many other criminal justice agencies as well. Many items on the POP Center

website are the product of applied research con-ducted by police departments. Therefore, crimi-nal justice professionals need to know not only how to interpret research accurately but also how to produce accurate research.

What Is This Book About?This book focuses on how we know what we know.

This book focuses on how we learn and know things, not on what we know. Although you will come away from the book knowing some things you don’t know right now, our primary purpose is to help you look at how you know things, not what you know.

Two RealitiesUltimately, we live in a world of two realities. Part of what we know could be called our “experiential reality”—the things we know from direct experience. For example, if you dive into a glacial stream fl owing down through the Canadian Rockies, you don’t need anyone to tell you that the water is cold; you notice that all by yourself. And the fi rst time you step on a thorn, you know it hurts even before anyone tells you. The other part of what we know could be called our “agreement reality”—the things we consider real because we’ve been told they’re real and everyone else seems to agree they are real. A big part of growing up in any society, in fact, is learning to accept what everybody around us “knows” to be true. If we don’t know those same things, we can’t really be a part of the group. If you were to seriously question a geography professor as to whether the sun re-ally sets in the west, you’d quickly fi nd yourself set apart from other people. The fi rst reality is a product of our own experience; the second is a product of what people have told us.

To illustrate the difference between agree-ment and experiential realities, consider pre-ventive police patrol. The term preventive im-plies that when police patrol their assigned beats they prevent crime. Police do not prevent all crime, of course, but it is a commonsense



Licensed to:


belief that a visible, mobile police force will pre-vent some crimes. In fact, the value of patrol in preventing crime was a fundamental tenet of police operations for many years. O.W. Wilson, a legendary police chief in Chicago and the au-thor of an infl uential book on police admin-istration, wrote that patrol was indispensable in preventing crime by eliminating incentives and opportunities for misconduct (Wilson and McLaren, 1963:320). A 1967 report on policing by President Lyndon Johnson’s Presi-dent’s Commission on Law Enforcement and Administration of Justice (1967:1) stated that “the heart of the police effort against crime is patrol. . . . The object of patrol is to disperse policemen in a way that will eliminate or re-duce the opportunity for misconduct and to increase the probability that a criminal will be apprehended while he is committing a crime or immediately thereafter.”

Seven years later, the Police Foundation, a private research organization, published results from an experimental study that presented a dramatic challenge to conventional wisdom. Known as the “Kansas City Preventive Patrol Experiment,” this classic study compared po-lice beats with three levels of preventive patrol: (1) control beats, with one car per beat; (2) proac-tive beats, with two or three cars per beat; and (3) reactive beats, with no routine preventive pa-trol. After almost 1 year, researchers examined data from the three types of beats and found no differences in crime rates, citizen satisfaction with police, fear of crime, or other measures of police performance (Kelling, Pate, Dieckman, and Brown, 1974).

Researchers and law enforcement profes-sionals alike were surprised by these fi ndings. For the record, the Kansas City researchers never claimed to have proved that preventive patrol had no impact on crime. Instead, they argued that police should work more closely

with community members and that routine pa-trol might be more effective if combined with other strategies that used police resources in a more thoughtful way.

Additional studies conducted in the 1970s cast doubt on other fundamental assumptions about police practices. A quick response to crime re-ports made no difference in arrests, according to a research study in Kansas City (Van Kirk, 1977). And criminal investigation by police detectives rarely resulted in an arrest (Greenwood, 1975).

We mention these examples not to attack routine law enforcement practices. Rather, we want to show that systematic research on po-licing has illustrated how traditional beliefs—agreement reality—can be misleading. Simply increasing the number of police offi cers on patrol does not reduce crime because police pa-trol often lacks direction. Faster response time to calls for police assistance does not increase arrests because there is often a long delay be-tween the time when a crime occurs and when it is reported to police. Clever detective work seldom solves crimes: investigators get most of their information from reports prepared by patrol offi cers, who, in turn, get their informa-tion from victims and witnesses.

Traditional beliefs about patrol effective-ness, response time, and detective work are examples of agreement reality. In contrast, the research projects that produced alternative views about each law enforcement practice rep-resent experiential reality. These studies are ex-amples of empirical1 research, the production of knowledge based on experience or observa-tion. In each case, researchers conducted stud-ies of police practices and based their conclu-sions on observations and experience. Empirical research is a way of learning about crime and criminal justice; explaining how to conduct em-pirical research is the purpose of this book.

In focusing on empirical research, we do not intend to downplay the importance of other ways

1Words set in boldface are defi ned in the glossary at the end of the book.

Empirical From experience. Social science is said to be empirical when knowledge is based on what we experience.



Licensed to:


of knowing things. Law students, for example, are trained in how to interpret statutes and judi-cial opinions. Historians take courses on meth-ods of historical interpretation, mathematics majors learn numerical analysis, and students of philosophy study logic. If you are a criminal jus-tice major, many of the other courses you take—say, a course on theories of crime and deviance—will add to your agreement reality.

The Role of ScienceScience offers an approach to both agreement reality and experiential reality. Scientists have certain criteria that must be met before they will agree on something they haven’t person-ally experienced. In general, an assertion must have both logical and empirical support: It must make sense, and it must agree with actual ob-servations. For example, why do earthbound scientists accept the assertion that it’s cold on the dark side of the moon? First, it makes sense because the surface heat of the moon comes from the sun’s rays. Second, scientifi c measure-ments made on the moon’s dark side confi rm the assertion. Therefore, scientists accept the reality of things they don’t personally experi-ence—they accept an agreement reality—but they have special standards for doing so.

More to the point of this book, however, sci-ence offers a special approach to the discovery of reality through personal experience. Episte-mology is the science of knowing; methodol-ogy (a subfi eld of epistemology) might be called “the science of fi nding out.” This book focuses on criminal justice methodology—how social science methods can be used to better under-stand crime and criminal justice problems. To understand scientifi c inquiry, let’s fi rst look at the kinds of inquiry we all do each day.

Personal Human InquiryEveryday human inquiry draws on personal experi-ence and secondhand authority.

Most of us feel more comfortable if we under-stand what’s going on around us and are able to

predict our future circumstances. We seem quite willing, moreover, to undertake this task using causal and probabilistic reasoning. First, we generally recognize that future circumstances are somehow caused or conditioned by present ones. For example, we learn that getting an edu-cation will affect how much money we earn later in life and that running stoplights may result in an unhappy encounter with an alert traffi c of-fi cer. As students, we learn that studying hard will result in better examination grades.

Second, we recognize that such patterns of cause and effect are probabilistic in nature: The effects occur more often when the causes occur than when the causes are absent—but not al-ways. Thus, as students, we learn that studying hard produces good grades in most instances, but not every time. We recognize the danger of ignoring stoplights without believing that ev-ery such violation will produce a traffi c ticket.

The concepts of causality and probability play a prominent role in this book. Science makes causality and probability more explicit and provides techniques for dealing with them more rigorously than does casual human in-quiry. Science sharpens the skills we already have by making us more conscious, rigorous, and explicit in our inquiries.

As we look at our own personal inquiry, it is useful to distinguish between prediction and understanding. Attempts to predict often occur in a context of knowledge and understanding. If we can understand why things are related to one another, why certain regular patterns occur, we can predict better than if we simply observe and remember those patterns. For example, college dormitories are often targets of burglary during semester breaks. If you understand something about the opportunity structure of burglary (it’s more likely when a suitably motivated offender knows that a dwelling will be unoccupied), you will be able to predict that hanging a sign on your room that says, “Off to Jamaica! See you

Methodology The study of methods used to understand something; the science of fi nding out.



Licensed to:


in two weeks!” invites trouble. Thus, human inquiry attempts to answer both what and why questions, and we pursue these goals by observ-ing phenomena and fi guring them out.

However, our attempts to learn about the world are only partly linked to personal inquiry and direct experience. Another, much larger, part comes from the agreed-on knowledge that others give us. This agreement reality both assists and hinders our attempts to fi nd out things for ourselves. Two important sources of secondhand knowledge—tradition and author-ity—deserve brief consideration here.

TraditionEach of us inherits a culture made up, in part, of fi rmly accepted knowledge about the work-ings of the world. We may learn from others that planting corn in the spring will result in the greatest assistance from the gods, that the circumference of a circle is approximately

twenty-two sevenths of its diameter, or that driving on the left side of the road (in the United States) is dangerous. We may test a few of these “truths” on our own, but we simply ac-cept the great majority of them. These are the things that “everybody knows.”

Tradition, in this sense, has some clear ad-vantages for human inquiry. By accepting what everybody knows, we are spared the overwhelm-ing task of starting from scratch in our search for regularities and understanding. Knowledge is cumulative, and an inherited body of infor-mation and understanding is the jumping-off point for the development of more knowledge.

At the same time, tradition may hinder human inquiry. If we seek a fresh understanding of some-thing everybody already understands and has al-ways understood, we may be marked as fools for our efforts. More to the point, however, it rarely occurs to most of us to seek a different under-standing of something we all “know” to be true.

ARREST AND DOMESTIC VIOLENCE

In 1983, preliminary results were released from a study on the deterrent effects of arrest in cases of domestic violence. The study reported that male abusers who were arrested were less likely to commit future assaults than offenders who were not arrested. Conducted by researchers from the Police Foundation, the study used rig-orous experimental methods adapted from the natural sciences. Criminal justice scholars gener-ally agreed that the research was well designed and executed. Public officials were quick to em-brace the study’s findings that arresting domestic violence offenders deterred them from future violence.

Here, at last, was empirical evidence to sup-port an effective policy in combating domestic assaults. Results of the Minneapolis Domes-tic Violence Experiment were widely dissemi-

nated, in part due to aggressive efforts by the researchers to publicize their findings (Sher-man and Cohn, 1989). The attorney general of the United States recommended that police departments make arrests in all cases of misde-meanor domestic violence. Within 5 years, more than 80 percent of law enforcement agencies in U.S. cities adopted arrest as the preferred way of responding to domestic assaults (Sherman, 1992:2).

Several things contributed to the rapid adop-tion of arrest policies to deter domestic violence. First, the experimental study was conducted carefully by highly respected researchers. Sec-ond, results were widely publicized in newspa-pers, in professional journals, and on television programs. Third, officials could understand the study, and most believed that its findings made



Licensed to:


AuthorityDespite the power of tradition, new knowl-edge appears every day. In addition to our own personal inquiries, throughout life we learn about the new discoveries and understandings of others. Our acceptance of this new knowl-edge often depends on the status of the dis-coverer. For example, you are more likely to be-lieve a judge who declares that your next traffi c violation will result in a suspension of your driver’s license than to believe your parents when they say the same thing.

Like tradition, authority can both help and hinder human inquiry. We do well to trust the judgment of individuals who have special training, expertise, and credentials in a matter, especially in the face of contradic-tory arguments on a given question. At the same time, inquiry can be greatly hindered by the legitimate authorities who err within

their own special province. Biologists, after all, do make mistakes in the fi eld of biology, and biological knowledge changes over time. Most of us assume that over-the-counter medications are safe when taken as directed, trusting the authority of drug manufacturers and government agencies. However, in the late nineteenth century, our trust might have led us to buy a bottle of Bayer Heroin, then avail-able as an over-the-counter pain relief medi-cation (Inciardi, 1986). The box titled “Arrest and Domestic Violence” illustrates the diffi -cult problems that can result when criminal justice policy makers accept too quickly the results from criminal justice research.

Inquiry is also hindered when we depend on the authority of experts speaking outside their realm of expertise. For example, consider the political or religious leader, lacking any bio-chemical expertise, who declares marijuana to

sense. Finally, mandating arrest in less serious cases of domestic violence was a straightforward and politically attractive approach to a growing problem.

Sherman and Berk (1984), however, urged caution in uncritically embracing the results of their study. Others urged that similar research be conducted in other cities to check on the Minneapolis findings (Lempert, 1984). Recog-nizing this, the U.S. National Institute of Justice sponsored more experiments—known as replica-tions—in six other cities. Not everyone was happy about the new studies. For example, a feminist group in Milwaukee opposed the replication in that city because it believed that the effective-ness of arrest had already been proved (Sherman and Cohn, 1989:138).

Results from the replication studies brought into question the effectiveness of arrest policies. In three cities, no deterrent effect was found in police records of domestic violence. In other cities, there was no evidence of deterrence for

longer periods (6–12 months), and in three cit-ies, researchers found that violence actually es-calated when offenders were arrested (Sherman, 1992: 30). For example, Sherman and associates (1992: 167) report that in Milwaukee “the initial deterrent effects observed for up to thirty days quickly disappear. By one year later [arrests] pro-duce an escalation effect.” Arrest works in some cases but not in others. As in many other cases, in responding to domestic assaults, it’s impor-tant to carefully consider the characteristics of offenders and the nature of the relationship be-tween offender and victim.

After police departments throughout the country embraced arrest policies following the Minneapolis study, researchers were faced with the difficult task of explaining why initial re-sults must be qualified. Arrest seemed to make sense; officials and the general public believed what they read in the papers and saw on televi-sion. Changing their minds by reporting complex findings was more difficult.



Licensed to:


be a dangerous drug. The advertising industry plays heavily on this misuse of authority by having popular athletes endorse various con-sumer products.

Both tradition and authority, then, are dou-ble-edged swords in the search for knowledge about the world. Simply put, they provide us with a starting point for our own inquiry, but they may lead us to start at the wrong point or push us in the wrong direction.

Errors in Personal Human InquiryEveryday personal human inquiry reveals a number of potential biases.

Aside from the potential dangers of relying on tradition and authority, we often stumble when we set out to learn for ourselves. Let’s consider some of the common errors we make in our own casual inquiries and then look at the ways sci-ence provides safeguards against those errors.

Inaccurate ObservationThe keystone of inquiry is observation. We can never understand the way things are without fi rst having something to understand. We have to know what before we can explain why. On the whole, however, people are rather sloppy observ-ers of the fl ow of events in life. We fail to ob-serve things right in front of us and mistakenly observe things that aren’t so. Do you recall, for example, what your instructor was wearing on the fi rst day of this class? If you had to guess now, what are the chances you would be right?

In contrast to casual human inquiry, scien-tifi c observation is a carefully directed activity. Simply making observations in a more deliber-ate way helps to reduce error. If you had gone

to the fi rst class meeting with a conscious plan to observe and record what your instructor was wearing, you’d have been more accurate.

In many cases, using both simple and com-plex measurement devices helps to guard against inaccurate observations. Suppose, for example, that you had taken a photograph of your instructor on the fi rst day. The photo would have added a degree of precision well be-yond that provided by unassisted human senses.

OvergeneralizationWhen we look for patterns among the specifi c things we observe around us, we often assume that a few similar events are evidence of a gen-eral pattern. The tendency to overgeneralize is probably greatest when there is pressure to reach a general understanding, yet overgeneral-ization also occurs in the absence of pressure. Whenever overgeneralization does occur, it can misdirect or impede inquiry.

Imagine you are a rookie police offi cer newly assigned to foot patrol in an urban neighbor-hood. Your sergeant wants to meet with you at the end of your shift to discuss what you think are the major problems on the beat. Eager to earn favor with your supervisor, you interview the manager of a popular store in a small shop-ping area. If the manager mentions vandalism as the biggest concern, you might report that vandalism is the main problem on your beat, even though other store managers believe that drug dealing is the main problem and that it contributes to local burglary, car break-ins, and robbery as well as vandalism. Overgeneraliza-tion would lead to misrepresentation and sim-plifi cation of the problems on your beat.

Criminal justice researchers guard against overgeneralization by committing themselves in advance to a suffi ciently large sample of obser-vations and by being attentive to how represen-tative those observations are. The replication of inquiry provides another safeguard. Replica-tion means repeating a study, checking to see whether similar results are obtained each time. The study may also be repeated under slightly

Replication Repeating a research study to test the fi ndings of an earlier study, often un-der slightly different conditions or for a differ-ent group of subjects. Replication results either support earlier fi ndings or cause us to question the accuracy of an earlier study.



Licensed to:


different conditions or in different locations. The box titled “Arrest and Domestic Violence” describes an example of why replication can be especially important in applied research.

Selective ObservationOne danger of overgeneralization is that it may lead to selective observation. Once we have concluded that a particular pattern exists and have developed a general understanding of why, we will be tempted to pay attention to future events and situations that correspond with the pattern and to ignore those that don’t. Racial, ethnic, and other prejudices are reinforced by selective observation.

Researchers often specify in advance the number and kind of observations to be made before marking a conclusion to a particular project. For example, if we wanted to learn whether women were more likely than men to support long prison sentences for sex offend-ers, we would have to make a specifi ed number of observations on that question. We might select 200 people to be interviewed. Even if the fi rst 10 women supported long sentences and the fi rst 10 men opposed them, we would continue to interview everyone selected for the study and record each observation. We would base our conclusion on an analysis of all the observations, not just those fi rst 20.

Illogical ReasoningPeople have various ways of handling observa-tions that contradict their judgments about the way things are. Surely one of the most remark-able creations of the human mind is “the excep-tion that proves the rule,” an idea that makes no sense at all. An exception can draw attention to a rule or to a supposed rule, but in no sys-tem of logic can it prove the rule it contradicts. Yet we often use this pithy saying to brush away contradictions with a simple stroke of illogic.

What statisticians call the “gambler’s fal-lacy” is another illustration of illogic in day-to-day reasoning. According to this fallacy, a consistent run of either good or bad luck is

presumed to foreshadow its opposite. Thus, an evening of bad luck at poker may kindle the be-lief that a winning hand is just around the cor-ner; many a poker player has stayed in a game too long because of that mistaken belief. Con-versely, an extended period of good weather may lead us to worry that it is certain to rain on our weekend picnic.

Although we all sometimes use embarrass-ingly illogical reasoning, scientists avoid this pitfall by using systems of logic consciously and explicitly. Chapters 2 and 4 examine the logic(s) of science in more depth.

Ideology and PoliticsCrime is, of course, an important social prob-lem, and a great deal of controversy surrounds policies for dealing with crime. Many people feel strongly one way or another about the death penalty, gun control, and long prison terms for drug users as approaches to reducing crime. There is ongoing concern about racial bias in police practices and sentencing policies. Ideological or political views on such issues can undermine objectivity in the research process. Criminal justice professionals may have partic-ular diffi culty separating ideology and politics from a more detached, scientifi c study of crime.

Criminologist Samuel Walker (1994:16) compares ideological bias in criminal justice research to theology: “The basic problem . . . is that faith triumphs over facts. For both liber-als and conservatives, certain ideas are unchal-lenged articles of faith, almost like religious be-liefs that remain unshaken by empirical facts.”

Most of us have our own beliefs about pub-lic policy, including policies for dealing with crime. The danger lies in allowing such beliefs to distort how research problems are defi ned and how research results are interpreted. The scientifi c approach to the study of crime and criminal justice policy guards against, but does not prevent, ideology and theology from color-ing the research process. In empirical research, so-called articles of faith are compared with experience.



Licensed to:


To Err Is HumanWe have seen some of the ways that we can go astray in our attempts to know and understand the world and some of the ways that science pro-tects its inquiries from these pitfalls. Social sci-ence differs from our casual, day-to-day inquiry in two important respects. First, social scien-tifi c inquiry is a conscious activity. Although we engage in continuous observation in daily life, much of it is unconscious or semiconscious. In social scientifi c inquiry, in contrast, we make a conscious decision to observe, and we stay alert while we do it. Second, social scientifi c inquiry is a more careful process than our casual ef-forts; we are more wary of making mistakes and take special precautions to avoid doing so.

Do social science research methods offer total protection against the errors that people commit in personal inquiry? No. Not only do individuals make every kind of error we’ve looked at, but social scientists as a group also succumb to the pitfalls and stay trapped for long periods of time.

Foundations of Social ScienceSocial scientifi c inquiry generates knowledge through logic and observation.

Science is sometimes characterized as “logico-empirical.” This ungainly term carries an im-portant message: The two pillars of science are (1) logic or rationality and (2) observation. A scientifi c understanding of the world must make sense and must agree with what we ob-serve. Both of these elements are essential to social science and relate to three key aspects of the overall scientifi c enterprise: theory, data collection, and data analysis.

As a broad generalization, scientifi c theory deals with the logical aspect of science, data collection deals with the observational aspect, and data analysis looks for patterns in what is observed. This book focuses mainly on issues related to data collection—demonstrating how to conduct empirical research—but social sci-ence involves all three elements. With this in

mind, Chapter 2 discusses the theoretical con-text of designing and executing research, and Chapter 13 presents a conceptual introduction to the statistical analysis of data. Figure 1.1 of-fers a schematic view of how the book addresses these three aspects of social science.

Let’s turn now to some of the fundamen-tal issues that distinguish social science from other ways of looking at social phenomena.

Theory, Not Philosophy or BeliefSocial scientifi c theory has to do with what is, not what should be. This means that scien-tifi c theory—and, more broadly, science itself— cannot settle debates on value or worth. Social science cannot determine, for example, whether prosecutors who are elected (as in most states) are “better” than prosecutors who are ap-pointed by a state offi cial (as in New Jersey) except in terms of some agreed-on criteria. We could determine scientifi cally whether elected or appointed prosecutors are more respected by the citizens they serve. But we could do that only if we agreed on some measures of citizen respect, and our conclusion would depend to-tally on the measures on which we agreed.

By the same token, if we agree that, say, conviction rate or average sentence length is a good measure of a prosecutor’s quality, then we will be in a position to determine scientifi -cally whether a prosecutor in one city is better or worse than a prosecutor in another city. Again, however, our conclusion will be inextricably tied to the agreed-on criteria. As a practical matter, however, people are seldom able to agree on cri-teria for determining issues of value, so science is seldom of any use in settling such debates.

We return to this point in Chapter 12 when we examine evaluation research. Criminal jus-tice research often involves studying whether programs achieve their intended goals. One of the biggest problems faced by evaluation re-searchers is getting people to agree on the crite-ria for success and failure. Yet such criteria are essential if social scientifi c research is to tell us anything useful about matters of value.



Licensed to:


Observation

Chapters 9–11

Planning to doresearch

Chapters 3–7

Sampling

Chapter 8

DATA COLLECTION

DATA ANALYSIS

Chapters 12–13

THEORY

Chapter 2

Mediaexposure

Victimizationexperience

Personalcommunication

networks

Personaland household

vulnerability

Fear of crime

Knowledgeof events

Knowledgeof victims

Neighborhoodconditions

34% 78%

66% 22%

x

y

y

xY = a + x1 + x2 + x3 + x4 + e

a

cd g

b

Figure 1.1 Social Science = Theory + Data Collection + Data Analysis



Licensed to:


As an example, consider the dilemma of how to identify a good parole offi cer. On the one hand, a parole offi cer whose clients are rarely cited for violations and returned to prison might be considered a good offi cer. However, parole offi cers might attain low vio-lation rates by ignoring misbehavior among clients they are supposed to supervise—in ef-fect, by not supervising them at all. Therefore, we might view a parole offi cer who frequently cites parolees for violations as being espe-cially attentive to his or her job. We might also consider other factors in judging parole of-fi cers. Someone who routinely cites parolees for trivial rule infractions would not neces-sarily be considered a good offi cer, especially if such actions swell already crowded prison populations. In a recent study of parole and community supervision of offenders, the Na-tional Research Council (2007) considered this dilemma in examining the purposes of parole.

Thus, social science can assist us in know-ing only what is and why. It can be used to ad-dress the question of what ought to be only when people agree on the criteria for deciding what makes one thing better than another. But this agreement seldom occurs. With that un-derstanding, let’s turn now to some of the fun-damentals that social scientists use to develop theories about what is and why.

RegularitiesUltimately, social science aims to fi nd patterns of regularity in social life. This assumes, of course, that life is regular, not chaotic or ran-dom. That assumption applies to all science, but it is sometimes a barrier for people when they fi rst approach social science.

Certainly, at fi rst glance, the subject mat-ter of the physical sciences appears to be more regular than that of the social sciences. A heavy object, after all, falls to earth every time we drop it. In contrast, a judge may sentence one person to prison and give another probation even though each is convicted of the same of-fense. Or driving 10 miles per hour over the

speed limit will produce a speeding ticket in Ohio but not in New Jersey.

A vast number of norms and rules in soci-ety create regularity. For example, only persons who have reached a certain age may obtain a driver’s license. In the National Hockey League, only men participate on the ice. Such informal and formal prescriptions, then, regulate, or regularize, social behavior.

In addition to regularities produced by norms and rules, social science deals with other types of regularities based on observation. For example, teenagers commit more crimes than middle-aged people. When males commit mur-der, they usually kill another male, but female murderers more often kill a male. On average, white urban residents view police more favor-ably than nonwhites do. Judges receive higher salaries than police offi cers. And probation of-fi cers have more empathy for the people they supervise than prison guards do.

What About Exceptions?The objection that there are always exceptions to any social regularity does not mean that the reg-ularity itself is unimportant. A police offi cer in a large city might earn more than a judge in a small town, but overall judges earn more than police offi cers. The pattern still exists. Social regulari-ties represent probabilistic patterns, and a general pattern does not have to be refl ected in 100 per-cent of the observable cases to be a pattern.

This rule applies in the physical as well as the social sciences. In genetics, for example, the mating of a blue-eyed person with a brown-eyed person will probably result in a brown-eyed offspring. The birth of a blue-eyed child does not challenge the observed regularity, how-ever. Rather, the geneticist states only that the brown-eyed offspring is more likely and, fur-thermore, that a brown-eyed offspring will be born in only a certain percentage of cases. The social scientist makes a similar, probabilistic prediction: that women overall are less likely to murder anybody, but when they do, their vic-tims are most often males.



Licensed to:


Aggregates, Not IndividualsSocial scientists primarily study social patterns rather than individual ones. All regular pat-terns refl ect the aggregate or combined actions and situations of many individuals. Although social scientists study motivations that affect individuals, aggregates are more often the subject of social science research.

A focus on aggregate patterns rather than on individuals distinguishes the activities of criminal justice researchers from the daily rou-tines of most criminal justice practitioners. Consider, for example, the task of processing and classifying individuals newly admitted to a correctional facility. Prison staff administer psychological tests and review the prior record of each new inmate to determine security risks, program needs, and job options. A researcher who is studying whether white inmates tended to be assigned to more desirable jobs than non-white inmates would be more interested in pat-terns of job assignment. The focus would be on aggregates of white and nonwhite persons rather than the assignment for any particular individual.

Social scientifi c theories, then, typically deal with aggregate, not individual, behavior. Their purpose is to explain why aggregate patterns of behavior are so regular even when the indi-viduals who perform them change over time. In another important sense, social science doesn’t even seek to explain people. Rather, it seeks to understand the systems within which people operate, the systems that explain why people do what they do. The elements in such systems are not people but variables.

A Variable LanguageOur natural attempts at understanding usu-ally take place at the concrete, idiosyncratic level. That’s just the way we think. Suppose someone says to you, “Women are too soft-hearted and weak to be police offi cers.” You are likely to “hear” that comment in terms of what you know about the speaker. If it’s your old

Uncle Albert, who, you recall, is also strongly opposed to daylight savings time, zip codes, and indoor plumbing, you are likely to think his latest pronouncement simply fi ts into his dated views about things in general. If, in con-trast, the statement comes from a candidate for sheriff who is trailing a female challenger and who has begun making other statements about women being unfi t for public offi ce, you may “hear” his latest comment in the context of this political challenge.

In both of these examples, we try to under-stand the thoughts of a particular, concrete individual. In social science, however, we go beyond that level of understanding to seek in-sights into classes or types of individuals. In the two preceding examples, we might use terms like old-fashioned or bigoted to describe the person who made the comment. In other words, we try to identify the actual individual with some set of similar individuals, and that identifi cation operates on the basis of abstract concepts.

One implication of this approach is that it enables us to make sense out of more than one person. In understanding what makes the big-oted candidate think the way he does, we can also learn about other people who are “like him.” This is possible because we have not been studying bigots as much as we have been study-ing bigotry.

Bigotry is considered a variable in this case because the level of bigotry varies. Some people in an observed group are more bigoted than others. Social scientists may be interested in understanding other variables that might cause bigotry to be high in one instance and low in another. However, bigotry is not the only vari-able here. Gender, age, and economic status also vary among members of the observed group.

Here’s another example: Consider the prob-lem of whether police should make arrests in cases of domestic violence. The object of a po-lice offi cer’s attention in handling a domestic assault is the individual case. Of course, each case includes at last two people, and police are concerned with preventing further harm to



Licensed to:


the parties involved. The offi cer must decide whether to arrest someone or to take some other action. The criminal justice researcher’s subject matter is different: Does arrest as a general policy prevent future assaults? The re-searcher may study an individual case (victim and offender), but that case is of interest only because arrest policy might be invoked, which is what the researcher is really studying.

This is not to say that criminal justice re-searchers don’t care about real people. They certainly do. Their ultimate purpose in study-ing domestic violence cases is to identify ways to protect potential victims from future assaults. But in this example, victims and of-fenders are most relevant for what they reveal about the effectiveness of the arrest policy. As researchers, our interest centers on variables and aggregates, not on individuals.

Variables and AttributesSocial scientists study variables and the at-tributes that compose them. Social scientifi c theories are written in a variable language, and people get involved mostly as the carriers of those variables. Here’s what social scientists mean by attributes and variables.

Attributes are characteristics or qualities that describe some object such as a person. Ex-amples are “bigoted,” “old-fashioned,” “mar-ried,” “unemployed,” and “intoxicated.” Any quality we might use to describe ourselves or someone else is an attribute.

Variables are logical groupings of attri-butes. Thus, for example, “male” and “female” are attributes, and “gender” is the variable composed of the logical grouping of those two attributes. The variable “occupation” is com-posed of attributes like “dentist,” “professor,” and “truck driver.” “Prior record” is a variable composed of a set of attributes such as “prior convictions,” “prior arrests without convic-

tions,” and “no prior arrests.” It’s helpful to think of attributes as the categories that make up a variable. Figure 1.2 provides a schematic view of what social scientists mean by vari-ables and attributes.

The relationship between attributes and variables lies at the heart of both description and explanation in science. For example, we might describe a prosecutor’s offi ce in terms of the variable “gender” by reporting the observed frequencies of the attributes “male” and “fe-male”: “The offi ce staff is 60 percent men and 40 percent women.” An incarceration rate can be thought of as a description of the variable “incarceration status” of a state’s population in terms of the attributes “incarcerated” and “not incarcerated.” Even the report of family income for a city is a summary of attributes composing the income variable: $37,124, $64,980, $86,000, and so forth.

The relationship between attributes and variables becomes more complicated as we try to explain things. Here’s a simple example in-volving two variables: type of defense attorney and sentence. For the sake of simplicity, let’s assume that the variable “defense attorney” has only two attributes: “private attorney” and “public defender.” Similarly, let’s give the vari-able “sentence” two attributes: “probation” and “prison.” Now let’s suppose that 90 percent of people represented by public defenders are sen-tenced to prison and the other 10 percent are sentenced to probation. And let’s suppose that 30 percent of people with private attorneys go to prison and the other 70 percent receive pro-bation. This is shown visually in Figure 1.3A.

Figure 1.3A illustrates a relationship be-tween the variables “defense attorney” and “sentence.” This relationship can be seen by the pairings of attributes on the two variables. There are two predominant pairings: (1) per-sons represented by private attorneys who are sentenced to probation and (2) persons repre-sented by public defenders who are sentenced to prison. But there are two other useful ways of viewing that relationship.

Variables Logical groupings of attributes. The variable “gender” is made up of the attri-butes “male” and “female.”



Licensed to:


First, imagine that we play a game in which we bet on your ability to guess whether a per-son is sentenced to prison or probation. We’ll pick the people one at a time (not telling you which ones we’ve picked), and you have to guess which sentence each person receives. We’ll do it for all 20 people in Figure 1.3A. Your best strategy in this case is to always guess prison because 12 out of the 20 people are categorized that way. Thus, you’ll get 12 right and 8 wrong, for a net success score of 4.

Now suppose that we pick a person from Figure 1.3A and we have to tell you whether the person has a private attorney or a public defender. Your best strategy now is to guess prison for each person with a public defender and probation for each person represented by a private attorney. If you follow that strategy,

you will get 16 right and 4 wrong. Your im-provement in guessing the sentence based on knowing the type of defense attorney illus-trates what it means to say that the variables are related. You would have made a probabilis-tic statement based on some empirical obser-vations about the relationship between type of lawyer and type of sentence.

Second, let’s consider how the 20 people would be distributed if type of defense attorney and sentence were unrelated. This is illustrated in Figure 1.3B. Notice that half the people have private attorneys and half have public defend-ers. Also notice that 12 of the 20 (60 percent) are sentenced to prison—6 who have private at-torneys and 6 who have public defenders. The equal distribution of those sentenced to proba-tion and those sentenced to prison no matter

Some Common Criminal Justice Concepts

FemaleProbation

ThiefGender

SentenceProperty crimeMiddle-aged

AgeAuto theft

Occupation

Two Different Kinds of Concepts

Variables Attributes

Gender FemaleSentence ProbationProperty crime Auto theftAge Middle-agedOccupation Thief

A. B.

C. The Relationship Between Variables and Attributes

Variables Attributes

Gender Female, male

Age Young, middle-aged, old

Sentence Fine, prison, probation

Property crime Auto theft, burglary, larceny

Occupation Judge, lawyer, thief

Figure 1.2 Variables and Attributes



Licensed to:


what type of defense attorney each person had allows us to conclude that the two variables are unrelated. Here, knowing what type of attor-ney a person had would not be of any value to you in guessing whether that person was sen-tenced to prison or probation.

Variables and RelationshipsWe will look more closely at the nature of the relationships between variables later in this book. For now, let’s consider some basic obser-vations about variables and relationships that illustrate the logic of social scientifi c theories and their use in criminal justice research.

Theories describe relationships that might logically be expected among variables. This ex-pectation often involves the notion of causation: A person’s attributes on one variable are expected to cause or encourage a particular attribute on an-other variable. In the example just given, having a private attorney or a public defender seemed to cause a person to be sentenced to probation or prison, respectively. Apparently, there is some-thing about having a public defender that leads people to be sentenced to prison more often than if they are represented by a private attorney.

Type of defense attorney and sentence are ex-amples of independent and dependent variables,

A. Defendants represented by public defenders are sentenced to prison more often than those represented by private attorneys.

Prison

Probation

Public DefenderPrivate Attorney

B. There is no relationship between type of attorney and sentence.

Prison

Probation

Public DefenderPrivate Attorney

SENTENCE

SENTENCE

DEFENSE ATTORNEY

DEFENSE ATTORNEY

Figure 1.3 llustration of Relationships Between Two Variables



Licensed to:


respectively. These two concepts are implicit in causation, which is the focus of explana-tory research. In this example, we assume that criminal sentences are determined or caused by something; the type of sentence depends on something and so is called the dependent variable. The dependent variable depends on an independent variable; in this case, sentence de-pends on type of defense attorney.

Notice, at the same time, that type of de-fense attorney might be found to depend on something else—our subjects’ employment status, for example. People who have full-time jobs are more likely to be represented by private attorneys than those who are unemployed. In this latter relationship, the type of attorney is the dependent variable, and the subject’s employ-ment status is the independent variable. In cause-and-effect terms, the independent variable is the cause, and the dependent variable is the effect.

How does this relate to theory? Our discus-sion of Figure 1.3 involved the interpretation of data. We looked at the distribution of the 20 people in terms of the two variables. In con-structing a theory, we form an expectation about the relationship between the two variables based on what we know about each. For exam-ple, we know that private attorneys tend to be more experienced than public defenders. Many people fresh out of law school gain a few years of experience as public defenders before they enter private practice. Logically, then, we would expect the more experienced private attorneys to be better able to get more lenient sentences for their clients. We might explore this question directly by examining the relationship between attorney experience and sentence, perhaps com-paring inexperienced public defenders with pub-lic defenders who have been working for a few years. Pursuing this line of reasoning, we could also compare experienced private attorneys with private attorneys fresh out of law school.

Notice that the theory has to do with the variables “defense attorney,” “sentence,” and “years of experience,” not with individual people per se. People are the carriers of those

variables. We study the relationship between the variables by observing people. Ultimately, however, the theory is constructed in terms of variables. It describes the associations that might logically be expected to exist between particular attributes of different variables.

Purposes of ResearchWe conduct criminal justice research to serve differ-ent purposes.

Criminal justice research, of course, serves many purposes. Explaining associations between two or more variables is one of those purposes; others include exploration, description, and application. Although a given study can have several purposes, it is useful to examine them individually because each has different implica-tions for other aspects of research design.

ExplorationMuch research in criminal justice is conducted to explore a specifi c problem. A researcher or offi cial may be interested in some crime or criminal justice policy issue about which little is known. Or perhaps an innovative approach to policing, court management, or corrections has been tried in some jurisdiction, and the researcher wishes to determine how common such practices are in other cities or states. An exploratory project might collect data on some measure to establish a baseline with which fu-ture changes will be compared.

For example, heightened concern with drug use might prompt efforts to estimate the level of drug abuse in the United States. How many people are arrested for drug sales or possession each year? How many high school seniors report using marijuana in the past week or the past month? How many hours per day do drug deal-ers work, and how much money do they make? These are examples of research questions in-tended to explore different aspects of the prob-lem of drug abuse. Exploratory questions may also be formulated in connection with criminal justice responses to drug problems. How many



Licensed to:


cities have created special police or prosecutor task forces to crack down on drug sales? What sentences are imposed on major dealers or on casual users? How much money is spent on treatment for drug users? What options exist for treating different types of addiction?

Exploratory studies are also appropri-ate when a policy change is being considered. Stricter enforcement of laws and longer prison sentences were common policy responses to drug abuse in the 1990s, and jails and pris-ons were soon fi lled with newly arrested and sentenced drug offenders. This prompted a search for alternatives to incarceration, such as diversion coupled with treatment. One of the fi rst questions public offi cials typically ask when they consider some new policy is “How have other cities (or states) handled this problem?

Exploratory research in criminal justice can be simple or complex, using a variety of meth-ods. For example, a mayor seeking to learn about drug arrests in his or her city might simply phone the police chief and request a report. In contrast, estimating how many high school seniors have used marijuana requires more so-phisticated survey methods. Since 1975, differ-ent federal agencies have conducted nationwide surveys of students regarding drug use.

DescriptionA key purpose of many criminal justice studies is to describe the scope of the crime problem or policy responses to the problem. A researcher or public offi cial observes and then describes what was observed. Criminal justice observa-tion and description, methods grounded in the social sciences, tend to be more accurate than the casual observations people may make about how much crime there is or how violent teenagers are today. Descriptive studies are of-ten concerned with counting or documenting observations; exploratory studies focus more on developing a preliminary understanding about a new or unusual problem.

Descriptive studies are frequently conducted in criminal justice. The FBI has compiled the

Uniform Crime Report (UCR) since the 1930s. UCR data are routinely reported in newspapers and widely interpreted as accurately describing crime in the United States. For example, 2008 UCR fi gures (Federal Bureau of Investigation, 2009) showed that Nevada had the highest rate of auto theft (611.6 per 100,000 residents) in the nation, and Maine had the lowest (89.3 per 100,000 residents).

Because criminal justice policy in the United States is almost exclusively under the control of state and local governments, many descriptive studies collect and summarize information from local governments. For ex-ample, since 1850 the federal government has conducted an annual census of prisoners in state and local correctional facilities. Like the decennial U.S. census, it gathers basic charac-teristics of a population—in this case, the pop-ulation of people in detention (jail or prison) and on probation or parole.

Descriptive studies in criminal justice have other uses. A researcher may attend meetings of neighborhood anticrime groups and observe their efforts to organize block watch commit-tees. These observations form the basis for a case study that describes the activities of neigh-borhood anticrime groups. Such a descriptive study might present information that offi cials and residents of other cities can use to promote such organizations themselves. Or consider re-search by Bruce Jacobs and associates (Jacobs et al., 2003) in which they describe the moti-vations for carjacking, how offenders select targets, and how carjacking differs from other types of robbery.

ExplanationA third general purpose of criminal justice re-search is to explain things. Recall our earlier example, in which we sought to explain the rela-tionship between type of attorney and sentence length. Reporting that urban residents have gen-erally favorable attitudes toward police is a de-scriptive activity, but reporting why some people believe that police are doing a good job while



Licensed to:


other people do not is an explanatory activity. Similarly, reporting why Nevada has the high-est auto theft rate in the nation is explanation; simply reporting auto theft rates for different states is description. A researcher has an explan-atory purpose if he or she wishes to know why the number of 14 year olds involved in gangs has increased, as opposed to simply describing changes in gang membership.

ApplicationResearchers also conduct criminal justice stud-ies of an applied nature. Applied research stems from a need for specifi c facts and fi ndings with policy implications. Another purpose of crimi-nal justice research, therefore, is its application to public policy. We can distinguish two types of ap-plied research: evaluation and problem analysis.

First, applied research is often used to evaluate the effects of specifi c criminal justice programs. Determining whether a program de-signed to reduce burglary actually had that in-tended effect is an example of evaluation. In its most basic form, evaluation involves comparing the goals of a program with the results. For ex-ample, if one goal of increased police foot patrol is to increase willingness to report crimes to police, then an evaluation of foot patrol might compare levels of reporting before and after increasing the number of police offi cers on the beat on foot. In most cases, evaluation research uses social science methods to test the results of some program or policy change. Because crime problems persist and seem to change frequently, offi cials are constantly seeking new approaches, and it is becoming more common for public offi cials or researchers to conduct evaluations of new programs.

The second type of applied research is prob-lem analysis. What would happen to court backlogs if we designated a judge and pros-ecutor who would handle only drug-dealing cases? How many new police offi cers would have to be hired if a department shifted to two-offi cer cars on night shifts? These are examples of what if questions addressed by

problem analysis. Answering such questions is sort of a counterpart to program evaluation. Problem analysis is different from other forms of criminal justice research primarily in its focus on future events. Rather than observing and analyzing current or past behavior, policy analysis tries to anticipate the future conse-quences of alternative actions.

Similarly, justice organizations are increas-ingly using techniques of problem analysis to study patterns of cases and devise appropriate responses. Problem-oriented policing is perhaps the best-known example, in which crime ana-lysts work with police and other organizations to examine recurring problems. Ron Clarke and John Eck (2005) have prepared a comprehensive guide for this type of applied research.

Our brief discussion of distinct research purposes is not intended to imply that research purposes are mutually exclusive. Many crimi-nal justice studies have elements of more than one purpose. Suppose you want to evaluate a new program to reduce bicycle theft at your university. First, you need some information that describes the problem of bicycle theft on campus. Let’s assume your evaluation fi nds that thefts from some campus locations have declined but that there was an increase in bikes stolen from racks outside dormitories. You might explain these fi ndings by noting that bi-cycles parked outside dorms tend to be unused for longer periods and that there is more com-ing and going among bikes parked near class-rooms. One option to further reduce thefts would be to install more secure bicycle racks. A policy analysis might compare the costs of installing the racks with the predicted savings resulting from a reduction in bike theft.

Differing Avenues for InquirySocial science research is conducted in a variety of ways.

There is no one way of doing criminal justice research. If there were, this would be a much shorter book. In fact, much of the power and



Licensed to:


potential of social science research lies in the many valid approaches it comprises.

Three broad and interrelated distinctions underlie many of the variations of social science research: (1) idiographic and nomothetic expla-nations, (2) inductive and deductive reasoning, and (3) quantitative and qualitative data. Al-though it is possible to see them as competing choices, a good researcher masters each of these orientations.

Idiographic and Nomothetic ExplanationsAll of us go through life explaining things; we do it every day. You explain why you did poorly or well on an exam, why your favorite team is winning or losing, and why you keep getting speeding tickets. In our everyday ex-planations, we engage in two distinct forms of causal reasoning—idiographic and nomothetic explanation—although we do not ordinarily distinguish them.

Sometimes, we attempt to explain a single situation exhaustively. Thus, for example, you may have done poorly on an exam because (1) you had forgotten there was an exam that day, (2) it was in your worst subject, (3) a traffi c jam caused you to be late to class, and (4) your roommate kept you up the night before with loud music. Given all these circumstances, it is no wonder that you did poorly on the exam.

This type of causal reasoning is idio-graphic explanation. Idio in this context means “unique, separate, peculiar, or distinct,” as in the word idiosyncrasy. When we complete an idiographic explanation, we feel that we fully understand the many causes of what happened in a particular instance. At the same time, the scope of our explanation is limited to the case at hand. Although parts of the idiographic ex-planation might apply to other situations, our intention is to explain one case fully.

Now consider a different kind of explanation. For example, every time you study with a group, you do better on an exam than if you study alone; or your favorite team does better at home

than on the road; or you get more speeding tick-ets on weekends than during the week. This type of explanation—called nomothetic—seeks to ex-plain a class of situations or events rather than a single one. Moreover, it seeks to explain “effi -ciently,” using only one or just a few explanatory factors. Finally, it settles for a partial rather than a full explanation of a type of situation.

In each of the preceding nomothetic exam-ples, you might qualify your causal statements with phrases like “on the whole” or “usually.” Thus, you usually do better on exams when you’ve studied in a group, but there have been exceptions. Similarly, your team has won some games on the road and lost some at home. And last week you got a speeding ticket on the way to Tuesday’s chemistry class, but you did not get one over the weekend. Such exceptions are an acceptable price to pay for a broader range of overall explanation.

Both the idiographic and the nomothetic approaches to understanding can be useful in daily life. They are also powerful tools for crimi-nal justice research. Thus, the researcher who seeks an exhaustive understanding of the inner workings of a particular juvenile gang or the rul-ings of a specifi c judge is engaging in idiographic research. The aim is to understand that particu-lar group or individual as fully as possible.

Rick Brown and Ron Clarke (2004) sought to understand thefts of a particular model of Nissan trucks in the south of England. Most stolen trucks were never recovered. Their re-search led Brown and Clarke to a shipping yard where trucks were taken apart and shipped to ports in France and Nigeria as scrap metal. They later learned that trucks were reassembled and sold to individuals and small companies. In the course of their research, they linked most thieves in England and most resellers abroad to legitimate shipping and scrap metal businesses. Even though Brown and Clarke sought answers to the idiosyncratic problem of stolen trucks in one region of England, they came to some tenta-tive conclusions about loosely organized inter-national theft rings.



Licensed to:


Sometimes, however, the aim is a more generalized understanding, across a class of events, even though the level of understanding is inevitably more superfi cial. For example, re-searchers who seek to uncover the chief factors that lead to juvenile delinquency are pursu-ing a nomothetic inquiry. They might discover that children who frequently skip school are more likely to have records of delinquency than those who attend school regularly. This expla-nation would extend well beyond any single juvenile, but it would do so at the expense of a complete explanation.

In contrast to the idiographic study of Nissan truck theft, Pierre Tremblay and asso-ciates (2001) explored how a theory of offend-ing helped explain different types of offender networks. Examining auto thefts over 25 years in Quebec, the authors concluded that dif-ferent types of relationships were involved in different types of professional car theft. How-ever, Tremblay and associates found that per-sons involved in legitimate car sales and repair businesses were key members in all networks. The researchers showed how complex relation-ships among people involved in legitimate and illegitimate activities helped explain patterns of car theft over a quarter-century. This is an illustration of the nomothetic approach to understanding.

Thus, social scientists have access to two distinct logics of explanation. We can alter-nate between searching for broad, albeit less detailed, universals (nomothetic) and prob-ing more deeply into more specifi c cases (idiographic). Both are good science, both are rewarding, and both can be fun.

Inductive and Deductive ReasoningThe distinction between inductive and deduc-tive reasoning exists in daily life, as well as in criminal justice research. You might take two different routes to reach the conclusion that you do better on exams if you study with others. Suppose you fi nd yourself puzzling, halfway through your college career, about why you do

so well on exams sometimes and more poorly at other times. You list all the exams you’ve taken, noting how well you did on each. Then you try to recall any circumstances shared by all the good exams and by all the poor ones. Did you do better on multiple-choice exams or essay exams? Morning exams or afternoon exams? Exams in the natural sciences, the humanities, or the social sciences? After you studied alone or in a group? It suddenly occurs to you that you almost always did better on exams when you studied with others than when you studied alone. This is known as the inductive mode of inquiry.

Inductive reasoning (induction) moves from the specifi c to the general, from a set of particular observations to the discovery of a pattern that represents some degree of order among the varied events under examina-tion. Notice, incidentally, that your discovery doesn’t necessarily tell you why the pattern exists—merely that it does.

There is the second, and very different, way you might reach the same conclusion about studying for exams. As you approach your fi rst set of exams in college, you might won-der about the best ways to study. You might consider how much you should review the readings and how much you should focus on your class notes. Should you study at a mea-sured pace over time or pull an all-nighter just before the exam? Among these musings, you might ask whether you should get together with other students in the class or study on your own. You decide to evaluate the pros and cons of both options. On the one hand, studying with others might not be as effi -cient because a lot of time might be spent on material you already know. Or the group might get distracted from studying. On the other hand, you can understand some-thing even better when you’ve explained it to someone else. And other students might understand material that you’ve been hav-ing trouble with and reveal perspectives that might have escaped you.



Licensed to:


So you add up the pros and the cons and conclude, logically, that you’d benefi t from studying with others. This seems reasonable to you in theory. To see whether it is true in prac-tice, you test your idea by studying alone for half your exams and studying with others for half. This second approach is known as the de-ductive mode of inquiry.

Deductive reasoning (deduction) moves from the general to the specifi c. It moves from

a pattern that might be logically or theo-retically expected to observations that test whether the expected pattern actually oc-curs in the real world. Notice that deduction begins with “why” and moves to “whether,” whereas induction moves in the opposite direction.

Both inductive and deductive reasoning are valid avenues for criminal justice and other social science research. Moreover, they work

P U T T I N G I T A L L T O G E T H E R

IntroductionRacial profi ling of drivers on the nation’s streets and highways became a prominent issue in the late 1990s. Concern was fueled by compelling stories of minority motorists stopped by police for minor traffi c violations, then subjected to aggressive questioning, searches, and even ar-rest. One of the most highly publicized examples involved:

. . . Robert Wilkins, a Harvard Law School graduate and a public defender in Wash-ington, D.C., who went to a family fu-neral in Ohio in May 1992. On the return trip, he and his aunt, uncle, and 29-year-old cousin rented a Cadillac for the trip home. His cousin was stopped for speed-ing in western Maryland while driving 60 miles per hour in a 55-mile-per-hour zone of the interstate. The group was forced to stand on the side of the inter-state in the rain for an extended period while offi cers and drug-sniffi ng dogs searched their car. Nothing was found. Wilkins, represented by the ACLU, fi led suit and received a settlement from the state of Maryland. (Ramirez, McDevitt, and Farrell, 2000:6)

What came to be known as “driving while black” generated a number of lawsuits and eventually legislation at the state and federal level.

The underlying question was whether police traffi c stops targeted African American and other minority drivers in a discriminatory way. Because the U.S. Constitution prohibits law enforcement offi cers from discriminatory behavior based on race, allegations of racial profi ling generated a number legal challenges and court cases.

By their nature, lawsuits revolve around indi-vidual cases, such as that of Robert Wilkins, and whether evidence of discrimination was present in Wilkins’s encounter with the Maryland State Police. In this sense, court cases tend to seek idio-graphic explanations of what happened in an indi-vidual case. Eventually, however, social scientists became involved in trying to assess the scope of racial profi ling and what sorts of things might be associated with the practice. And social scien-tists focused more on nomothetic explanations of what kinds of things accounted for more general patterns of police actions in traffi c stops.

Racial profi ling also offers examples of differ-ent types of errors in traditional human inquiry. You might recognize the role overgeneralization plays in most forms of prejudice. Selective obser-vation is another example. If police believe minor-ities are more often involved in drug or weapons smuggling, they will selectively stop cars driven by minorities. Assuming the extreme case where police stop only minorities, they will only be able to detect possible weapons or drug offenses

“DRIVING WHILEBLACK”



Licensed to:


together to provide ever more powerful and complete understandings.

Quantitative and Qualitative DataSimply put, the distinction between quanti-tative and qualitative data is the distinction between numerical and non-numerical data. When we say that someone is witty, we are making a qualitative assertion. When we say that that person has appeared three times in a

local comedy club, we are adding quantitative evidence to our assertion.

Most observations are qualitative at the out-set, whether it is our experience of someone’s sense of humor, the location of a pointer on a measuring scale, or a check mark entered in a questionnaire. None of these things is inherently numerical. But it is often useful to convert obser-vations to a numerical form. Quantifi cation of-ten makes our observations more explicit, makes

among minority motorists. In that case, race pro-fi ling might become a self-fulfi lling prophecy.

This box is the fi rst of a running example that appears throughout the book. We examine racial profi ling for several reasons. First, it was a highly publicized issue that promoted policy action and research throughout the United States. Sec-ond, for most people, a traffi c stop is their most common experience of coming under suspicion of police. A much larger proportion of people have a contact with police through a traffi c stop than a criminal arrest. Further, in the words of David Harris (1999), “almost any black person any place in the country” could describe a per-sonal experience of what was believed to be a discriminatory traffi c stop. Third, police and other public offi cials challenged accusations of discrimination, claiming any disproportionate traffi c stops of black motorists refl ected differ-ent rates of traffi c violations. This raised ques-tions about how to determine whether individ-ual traffi c stops or patterns of traffi c stops were based on the race of drivers or on something else. In this way, measuring patterns of traffi c stops and the reasons underlying those patterns became an important research topic.

Finally, researchers at New Jersey’s Rutgers University conducted their own research on race profi ling in New Jersey, a state that came to sym-bolize race profi ling for many people. Maxfi eld collaborated with colleagues George Kelling and Carsten Andresen to conduct research on the New Jersey State Police (Maxfi eld and Andresen, 2002; Maxfi eld and Kelling, 2005). And Carsten Andresen completed his own dissertation research

on this topic (Andresen, 2005). Thus, the running example refl ects some direct experiences in the messy realities of criminal justice research, realities that are not usually depicted in published studies.

How Do We Know?Let’s consider what we have covered so far and examine how these general issues in research are refl ected in the questions about racial profi ling on the nation’s highways.

■ What percentage of cars stopped have minor-ity drivers (descriptive)? What affects police decisions to stop particular vehicles (explana-tory)? What changes should be made in police practices regarding traffi c stops (applied)?

■ How do we come to believe that discrimina-tory practices underlie patterns of police traffi c stops? What evidence supports that belief? And what evidence supports claims that police actions are not affected by race or ethnicity?

■ In addition to those mentioned above, what errors of traditional human inquiry might be involved? What about ideology and politics?

■ Are particular theories available to guide our inquiry?

■ Quite a lot of research has been conducted on municipal policing and police actions with respect to crime, but state police and traffi c enforcement have hardly been studied at all. Can fi ndings from other police actions help understand traffi c enforcement?

How might the problem of racial profi ling illus-trate other topics described in this chapter?



Licensed to:


it easier to aggregate and summarize data, and opens up the possibility of statistical analyses, ranging from simple descriptions to more com-plex testing of relationships between variables.

Quantifi cation requires focusing our atten-tion and specifying meaning. Suppose some-one asks whether your friends tend to be older or younger than you. A quantitative answer seems easy. You think about how old each of your friends is, calculate an average, and see whether it is higher or lower than your own age. Case closed.

Or is it? Although we focused our attention on “older or younger” in terms of the num-ber of years people have been alive, we might mean something different with that idea—for example, “maturity” or “worldliness.” Thus, your friends may tend to be a little younger than you in age but to act more mature. Or we might have been thinking of how young or old your friends look or of the variation in their life experiences, their worldliness. All these other meanings are lost in the numerical calculation of average age.

In addition to greater detail, non-numerical observations seem to convey a greater richness of meaning than do quantifi ed data. Think of the cliché “He is older than his years.” The meaning of that expression is lost in attempts to specify how much older. In this sense, the richness of meaning is partly a function of am-biguity. If the expression meant something to you when you read it, that meaning came from your own experiences, from people you have known who might fi t the description of being “older than their years.” Two things are certain: (1) Your understanding of the expression is dif-ferent from ours, and (2) you don’t know ex-actly what either of us means by the expression.

A psychology graduate student at John Jay College in New York City, Miriam G. was born in Frankfurt, Germany. Her mother was a child soldier in the civil confl ict that eventu-ally formed Eritrea from a region of Ethiopia in the Horn of Africa. An uncle in Saudi Ara-bia helped Miriam’s mother obtain asylum in

Germany, where she met the man who was to become Miriam’s father. Her parents divorced when Miriam was about 7 years old; her father moved to Las Vegas while she stayed with her mother. Miriam was increasingly unsettled by the acute brand of prejudice faced by many im-migrants in Germany, especially those from Muslim countries. After eventually overcom-ing strong objections from her mother, Miriam moved to the United States to join her father; she was 14 years old. Miriam obtained her un-dergraduate degree from the University of Ne-vada and set out for New York in September 2009 to begin her graduate work.

We would probably agree that Miriam sounds like someone who is both worldly and “older than her years.” However, the brief description of Miriam’s experiences, although it fl eshes out the meaning of the phrase, still does not equip us to say how much older or even to compare Miriam with someone else without the risk of disagree-ing as to which one is more “worldly.”

This concept can be quantifi ed to a certain extent, however. For example, we could make a list of life experiences that contribute to what we mean by “worldliness”:

Getting marriedGetting divorcedHaving a parent dieBeing arrestedBeing fi red from a job

We could quantify people’s worldliness by counting how many of these experiences they have had: the more such experiences, the more worldly we say they are. If we think that some experiences are more powerful than others, we can give those experiences more points than others. Once we decide on the specifi c experi-ences to be considered and the number of points each warrants, scoring people and comparing their worldliness is fairly straightforward.

To quantify a concept like “worldliness,” we must be explicit about what we mean. By focus-ing specifi cally on what we will include in our measurement of the concept, as we did here, we



Licensed to:


also exclude the other possible meanings. Inev-itably, then, quantitative measures will be more superfi cial than qualitative descriptions. This is the trade-off.

What a dilemma! Which approach should we choose? Which is better? Which is more ap-propriate to criminal justice research?

The good news is that we don’t have to choose. In fact, by choosing to undertake a qualitative or quantitative study, researchers run the risk of artifi cially limiting the scope of their inquiry. Both qualitative and quantitative methods are useful and legitimate. And some research situations and topics require elements of both approaches.

The box “Putting It All Together: Driving While Black” presents the fi rst installment of an example of criminal justice research we will consider throughout the book. This run-ning example will illustrate some features of topics discussed in each chapter, drawing largely on research completed by Maxfi eld and colleagues at Rutgers University. In this chapter’s example we introduce the topic and compare how researchers approach it to how it has been presented in courts and the media generally.

Knowing Through Experience: Summing Up and Looking AheadEmpirical research involves measurement and inter-pretation.

This chapter introduced the foundation of criminal justice research: empirical research, or learning through experience. Each avenue for inquiry—nomothetic or idiographic descrip-tion, inductive or deductive reasoning, quali-tative or quantitative data—is fundamentally empirical. It’s worth keeping that in mind as we examine the various forms criminal justice research can take.

It is also helpful to think of criminal jus-tice research as organized around two basic

activities: measurement and interpretation. Re-searchers measure aspects of reality and then draw conclusions about the meaning of what they have measured. All of us are observing all the time, but measurement refers to some-thing more deliberate and rigorous. Part Two of this book describes ways of structuring ob-servations to produce more deliberate, rigorous measures. Our ability to interpret observations in criminal justice research depends crucially on how those observations are structured. After deciding how to structure observations, we have to actually measure them. Whereas physical scientists sometimes use tensiometers, spectro-graphs, and other such equipment for measure-ment, criminal justice researchers use a variety of techniques, examined in Part Three.

The other key to criminal justice research is interpretation. Much of interpretation is based on data analysis, which is introduced in Part Four. More generally, however, interpreta-tion is very much dependent on how observa-tions are structured, a point we will encounter repeatedly.

When we put the pieces together—measure-ment and interpretation—we are in a position to describe, explain, or predict something. And that is what social science is all about.

Summary

• Knowledge of research methods is valuable to criminal justice professionals as consumers and producers of research.

• The study of research methods is the study of how we know what we know.

• Inquiry is a natural human activity for gaining an understanding of the world around us.

• Much of our knowledge is based on agreement rather than on direct experience.

• Tradition and authority are important sources of knowledge.

• Empirical research is based on experience and produces knowledge through systematic obser-vation.

• Whereas people often observe inaccurately, sci-ence avoids such errors by making observation a careful and deliberate activity.



Licensed to:


• Sometimes we jump to general conclusions on the basis of only a few observations. Scientists avoid overgeneralization through replication.

• Scientists avoid illogical reasoning by being as careful and deliberate in their thinking as they are in their observations.

• The scientifi c study of crime guards against, but does not prevent, ideological and political beliefs from infl uencing research fi ndings.

• Social science involves three fundamental as-pects: theory, data collection, and data analysis.

• Social scientifi c theory addresses what is, not what should be.

• Social scientists are interested in explaining aggregates, not individuals.

• Although social scientists observe people, they are primarily interested in discovering relation-ships that connect variables.

• Explanations may be idiographic or nomothetic.

• Data may be quantitative or qualitative.

• Theories may be inductive or deductive.

Key TermsAggregate (p. 15)Attribute (p. 16) Deductive reasoning (p. 24)Dependent variable (p. 19)Empirical (p. 6)Idiographic (p. 22)Independent variable (p. 19)Inductive reasoning (p. 23)Methodology (p. 7)Nomothetic (p. 22)Replication (p. 10) Variable (p. 16)

Review Questions and Exercises1. Review the common errors of personal inquiry

discussed in this chapter. Find a newspaper or magazine article about crime that illustrates one or more of those errors. Discuss how a sci-entist would avoid making that error.

2. Briefl y discuss examples of descriptive research and explanatory research about crime rates in a large city near your college or university.

3. Often, things we think are true and supported by considerable experience and evidence turn out not to be true, or at least not true with the certainty we expected. Criminal justice seems

especially vulnerable to this phenomenon, per-haps because crime and criminal justice policy are so often the subjects of mass and popular media attention. If news stories, movies, and TV shows all point to growing gang or drug-related violence, it is easy to assume that these are real problems identifi ed by systematic study. Choose a criminal justice topic or claim that’s currently prominent in news stories or entertainment. Consult a recent edition of the Sourcebook of Criminal Justice Statistics (cited in “Additional Readings”) for evidence to refute the claim.

Online Sessions for Chapter 1Online Sessions present further examples of se-lected material covered in each chapter. Your instructor may choose to use these for in-class dis-cussion (as I do with my students), or you can ac-cess them at home. To ensure that you always have access to live, correct links for the websites de-scribed here, we provide the necessary links on the companion website for Research Methods for Criminal Justice and Criminology at http://www.cengage.com/criminaljustice/maxfi eld. Once at the companion website, select this specifi c chapter, click on “Chap-ter Resources,” then click on “Web Links.”

Theory See the problem-solving guide by Ron Clarke and John Eck (2005) at the POP Center website. Module 8 (they don’t use chap-ters or pages) introduces some theoretical con-cepts that underlie environmental criminology. Then these principles are recommended as a ba-sic framework for problem analysis. Select one example each of a violent and property crime problem; then discuss how the crime triangle in module 8 helps you understand the problem. http://popcenter.org/learning/60steps/#

Purposes of Research Description: Most pub-lications on the Bureau of Justice Statistics (BJS) website are examples of descriptive research. Browse through the BJS website; then select a publication and summarize its stated research purpose. http://www.ojp.usdoj.gov/bjs/

Exploration: Some BJS publications present in-formation about new or evolving problems. Some-times you can fi nd an example of exploratory re-search. The publication “Identity Theft, 2005” is an



Licensed to:


example. Browse through the publication and de-scribe examples of exploration in the report. http://www.ojp.usdoj.gov/bjs/abstract/it05.htm

Explanation: The POP Center website contains a large selection of guides for specifi c police prob-lems. Select guide one and fi nd the section titled something like “Factors contributing to . . .” In most cases, the dependent variable will be named in the title. Identify two independent variables that affect the problem. Briefl y describe the ways in which these independent variables appear to op-erate. http://www.popcenter.org

Application: Later sections of POP Center prob-lem guides describe examples of actions that have been shown to be effective (or not effective) in the past. These are examples of applied research and are usually keyed in some way to independent vari-ables. Briefl y describe one effective and one not-so-effective intervention that correspond with the independent variables you selected above. http://www.popcenter.org

Variables and Attributes Select a BJS pub-lication that presents descriptive research.

Identify at least two variables and the attri-butes associated with those variables. http://www.ojp.usdoj.gov/bjs/

Finding and Assessing Information The web is an essential research tool. It’s diffi cult to think of a topic that cannot be readily exam-ined through web-based research. However, the vast number of websites can be uneven sources of information. Web blogs, for example, are of-ten geared to particular ideologies and points of view. Most of us have been solicited through phishing attempts masquerading as legitimate websites. The University of California at Berke-ley offers guidance on how to evaluate the qual-ity and legitimacy of websites. After reviewing materials on the Berkeley website, fi nd an exam-ple of a criminal justice website that you think is informative and legitimate. Then fi nd one that is guided by ideological or political views. http://www.lib.berkeley.edu/TeachingLib/Guides/Internet/FindInfo.html



Research Methods for Criminal Justice and Criminology, 6th...

Documents

Transcript of Research Methods for Criminal Justice and Criminology, 6th...